Backhaul Alternatives for 4G/5G HetNet Base Stations Part 1
Table 1 contrasts the types of base station, deployment scenarios, and the toolbox of possible wireless backhaul solutions. It shows that backhaul throughput for each base
Base station deployment optimization method based on dynamic adjustment quantum genetic algorithm
Gou et al. proposed an efficient micro base station deployment strategy by jointly optimizing the number, location, and power of micro base stations, optimizing trade-offs under different user distribution probabilities to enhance adaptability to various user distribution scenarios.
Moreover, we propose a dynamically adjusted quantum genetic algorithm (DAQGA) to optimize base station layout, with coverage and construction cost as objective functions. A signal reception strength metric is introduced to evaluate the effectiveness of the optimal layout.
Ratheesh et al. proposed a BS-Relay Station deployment technology based on joint clustering. The algorithm takes into account network throughput and coverage to achieve BS-Relay Station deployment. From the perspective of energy and the environment, the power that a BS consumes is proportional to the maximum region that the BS can serve .
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